Regional databases demonstrate macroecological patterns less clearly than systematically collected field data

IF 4.7 1区 环境科学与生态学 Q1 BIODIVERSITY CONSERVATION Ecography Pub Date : 2025-03-19 DOI:10.1111/ecog.07355
Matthew R. Kerr, Nicole Currie, Matthew A. Kosnik, John Alroy
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Abstract

The analysis of macroecological patterns has necessitated the use of large, composite datasets recording local-scale species occurrences distributed across the globe. These datasets, however, have various spatial and temporal biases, including taxonomic under sampling, range gaps for many species, and geographic uncertainty. They have rarely been compared to data collected in the field across large spatial gradients. In this paper we use two datasets built from online repositories plus standardised field collections of death assemblages to reconstruct macroecological patterns for marine bivalves along the eastern coastline of Australia – spanning over 20° of latitude and the transition between tropical and temperate regions. We test the strength of the latitudinal diversity gradient using four diversity measures and identify a biogeographical boundary. The field collection demonstrates a strong latitudinal gradient, but results from the composite datasets were varied. Adding observation-based records to the composite dataset obscured the latitudinal gradient. The location of the biogeographic boundary was the same in all datasets, and the location mirrored two previously published bioregionalisations. Although broad patterns seen in the field can be uncovered from composite macroecological datasets, care both in dataset construction and choice of methods is needed to ensure robust results.

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区域数据库显示的宏观生态模式不如系统收集的实地数据清晰
宏观生态模式的分析需要使用大型的复合数据集,记录分布在全球各地的局地尺度的物种发生情况。然而,这些数据集存在各种空间和时间偏差,包括分类采样不足、许多物种的范围差距和地理不确定性。很少将它们与跨大空间梯度的野外收集的数据进行比较。在本文中,我们使用了两个数据集,这些数据集来自在线存储库和标准化的死亡组合现场收集,以重建澳大利亚东部海岸线的海洋双壳类宏观生态模式——跨越20°纬度和热带和温带之间的过渡。采用四种多样性测量方法对纬度多样性梯度强度进行了检验,并确定了生物地理边界。野外数据集显示出很强的纬度梯度,但综合数据集的结果却各不相同。将基于观测的记录添加到复合数据集中会模糊纬度梯度。生物地理边界的位置在所有数据集中都是相同的,并且该位置反映了先前发表的两个生物区域化。尽管可以从复合宏观生态数据集中发现该领域的广泛模式,但需要在数据集构建和方法选择方面保持谨慎,以确保稳健的结果。
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来源期刊
Ecography
Ecography 环境科学-生态学
CiteScore
11.60
自引率
3.40%
发文量
122
审稿时长
8-16 weeks
期刊介绍: ECOGRAPHY publishes exciting, novel, and important articles that significantly advance understanding of ecological or biodiversity patterns in space or time. Papers focusing on conservation or restoration are welcomed, provided they are anchored in ecological theory and convey a general message that goes beyond a single case study. We encourage papers that seek advancing the field through the development and testing of theory or methodology, or by proposing new tools for analysis or interpretation of ecological phenomena. Manuscripts are expected to address general principles in ecology, though they may do so using a specific model system if they adequately frame the problem relative to a generalized ecological question or problem. Purely descriptive papers are considered only if breaking new ground and/or describing patterns seldom explored. Studies focused on a single species or single location are generally discouraged unless they make a significant contribution to advancing general theory or understanding of biodiversity patterns and processes. Manuscripts merely confirming or marginally extending results of previous work are unlikely to be considered in Ecography. Papers are judged by virtue of their originality, appeal to general interest, and their contribution to new developments in studies of spatial and temporal ecological patterns. There are no biases with regard to taxon, biome, or biogeographical area.
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